The present invention is in the field of wireless communication in a mobile communication system using relay stations.
Conventional relaying concepts comprise, for example, standard relaying methods as amplify-and-forward relaying, decode-and-forward relaying, respectively. While amplify-and-forward relaying has low delay on the expense of noise amplification, decode-and-forward relaying causes a processing delay at the relay station, due to decoding. Moreover, decoding errors at the relay station may have detrimental effects on decoding at the destination.
The designated purpose of a relay station in wireless networks is to facilitate the transmission of other users within the same cell, where one important benefit is provision of cooperative diversity as shown by A. Sendonaris, E. Erkip, and B. Aazhang, “Increasing uplink capacity via user cooperation diversity,” in Proc. IEEE Int. Symp. on Information Theory, 1998. While the concept of network coding as shown by R. Ahlswede, N. Cai, S. R. Li, and R. W. Yeung, “Network information flow,” IEEE Trans. Inf. Theory, vol. 46, no. 4, pp. 1204-1216, April 2000 was originally developed to increase throughput in wireline networks, the application of network coding to wireless networks has been shown to effectively combat the effects of the fading channels shown by X. Bao and J. Li, “Matching code-on-graph with network-on-graph: Adaptive network coding for wireless relay networks,” in Proc. 43rd Ann. Allerton Conf. on Communications, Control, and Computing, 2005, C. Hausl, F. Schreckenbach, I. Oikonomidis, G. Bauch, “Iterative network and channel decoding on a tanner graph,” in Proc. 43rd Ann. Allerton Conf. on Communications, Control, and Computing, 2005 and Y. Chen, S. Kishore, and J. Li, “Wireless diversity through network coding,” in Proc. IEEE Wireless Communications and Networking Conf., 2006 and L. Xiao, T. E. Fuja, J. Kliewer, and D. J. Costello, Jr., “Nested codes with multiple interpretations,” in Proc. 40th Ann. Conf. on Information Sciences and Systems, 2006, thereby providing cooperative diversity.
A common assumption is that the relay node or relay station can recover the source messages perfectly, thus restricting the investigation to relaying protocols based on the decode-and-forward (DF) as shown by the strategy of T. M. Cover and A. A. El Gamal, “Capacity theorems for the relay channel,” IEEE Trans. Inf. Theory, vol. IT-25, no. 5, pp. 572-584, September 1979, G. Kramer, M. Gastpar, and P. Gupta, “Cooperative strategies and capacity theorems for relay networks,” IEEE Trans. Inf. Theory, vol. 51, no. 9, pp. 3037-3063, September 2005, and L. Sankaranarayanan, G. Kramer, and N. B. Mandayam, “Hierarchical sensor networks: Capacity bounds and cooperative strategies using the multiple-access relay network,” in IEEE Conf. on Sensor Networks, 2004, or to the strategy that the relay does not transmit at all if residual errors remain after decoding, provided there exists an error detection scheme at the relay node.
FIG. 13 illustrates a scenario and a radio network which utilizes multi-hop relaying. FIG. 13 shows a source s1 transmitting a symbol or a transmit word x1, which is received by a relay station r and a destination d. FIG. 13 shows a second source s2 transmitting a second symbol or a transmit word x2, which is also received by the relay station r and a destination d. Moreover, the relay station r transmits a symbol xr, which is also received by the destination.
Throughout, the multiple-access relay channel (MARC=Multiple Access Relay Channel) shown in FIG. 13 with two sources s1, s2, one relay r and the destination d will be considered. The network geometry is assumed to be such that the relay is closer to the destination than to the sources, so that the source-relay channel quality is too low to permit reliable decoding at the relay. The relay-destination link, however, can support a higher rate due to its proximity to the destination. For such a scenario, the relay can make use of ideas from network coding as described by R. Ahlswede, N. Cai, S. R. Li, and R. W. Yeung, “Network information flow,” IEEE Trans. Inf. Theory, vol. 46, no. 4, pp. 1204-1216, April 2000 to form the log-likelihood ratios (LLRs) of the network coded message x1⊕x2 and transmit these LLRs in an analog manner to the destination to significantly increase the receiver performance, as shown in S. Yang and R. Koetter, “Network coding over a noisy relay: a belief propagation approach,” in Proc. IEEE Int. Symp. on Information Theory, 2007.
Other approaches with respect to relaying can be found in A. D. Wyner and J. Ziv, “The rate-distortion function for source coding with side information at the decoder,” IEEE Trans. Inf. Theory, vol. IT-22, no. 1, pp. 1-10, January 1976, A. Chakrabarti, A. de Baynast, A. Sabharwal, and B. Aazhang, “Half-duplex estimate-and-forward relaying: Bounds and code design,” in Proc. IEEE Int. Symp. on Information Theory, 2006, pp. 1239-1243, N. Tishby, F. C. Pereira, and W. Bialek, “The information bottleneck method,” in Proc. 37th Ann. Allerton Conf. on Communications, Control, and Computing, 1999, and G. Zeitler, R. Koetter, G. Bauch, and J. Widmer, “Design of network coding functions in multihop relay networks,” in Proc. 5th symposium Turbo Codes and Related Topics, 2008.
In E. Ayanoglu, et. al. “Diversity Coding of Transparent Self-Healing and Fault Tolerant Communication Networks”, IEEE Transactions on Communications, Vol. 41, No. 11, November 1993, the authors disclose the concept of network coding, which is illustrated in FIG. 14. FIG. 14 shows a first encoder 1410 coding an information word u1 to a first symbol or transmit word x1, which is transmitted to a relay station 1450 and a destination 1470. Furthermore, FIG. 14 shows a second encoder 1420, which encodes a second information word u2 to a second symbol or transmit word x2, which is also transmitted to the relay station 1450 and the destination 1470. As indicated in FIG. 14 at the relay station 1450, two symbols are received, superimposed by additive white Gaussian noise nr (AWGN=Additive White Gaussian Noise). Two decoders are operative at the relay station 1450, which are labeled “decoder 1” 1451 and “decoder 2” 1452 in FIG. 14.
Ideally, the two decoders 1451 and 1452 decode the information words u1 and u2. The two decoded information words are then combined as indicated by addition 1453 in FIG. 14 and the combination is encoded by the encoder 1454 shown in FIG. 14. The encoded combined symbol xR is then transmitted from the relay station 1450 to the destination 1470, where it is superimposed by AWGN nB. Three symbols or receive words are received at the destination 1470, namely y1 from “encoder 1” 1410, y2 from “encoder 2” 1420, and yR from the relay station 1450. At the destination 1470 joint decoding may be utilized in order to decode the information words u1 and u2. One disadvantage of the concept illustrated in FIG. 14 is the delay, which is associated with decoding the received signal at the relay station 1450 in order to derive the information words and with encoding the combination of said information words again at the relay station 1450.
Another conventional approach is illustrated in FIG. 15. FIG. 15 shows similar components as have been described with respect to FIG. 14, however, at the relay station 1450, instead of combining the decoded information words u1 and u2, a joint encoder 1455 is utilized. The joint encoder 1455 may have the advantage that an increased block length can be used, which may particularly be beneficial for iterative decoding. The joint encoder 1455 may enable increased diversity which may be exploited at the joint decoder at the destination 1470. However, high delays are still involved with decoding the received signals at the relay station and jointly encoding the decoded signals again, especially when increased block lengths are used. Another problem arises from decoding errors at the relay station 1450, which are re-encoded, and therewith extended or forwarded to the destination 1470.
Yet another conventional approach is illustrated in FIG. 16, which shows similar components as have already been introduced with respect to FIGS. 14 and 15. FIG. 16 illustrates the approach of analog transmission from the relay station 1450 to the destination 1470, which may, for example, be implemented at a base station or a NodeB. The main difference with respect to the above explained concepts is that the decoders 1451 and 1452 at the relay station 1450 provide soft information in terms of log likelihood ratios (LLR=Log Likelihood Ratio) of the information words u1 and u2. An equation is shown at the top of FIG. 16, which provides insight into a LLR of a general information word u. In a general case, the information word u may comprise only a single bit, which can take two values, namely +1 or −1. The so-called soft information can be determined by considering the quotient of the probability that the bit equals +1 and the probability that the bit equals −1, which is shown in the equation at the top of FIG. 16.
Taking the logarithm of the quotient linearizes the soft information and maps the quotient from the range of positive real number to the full range of the real numbers. Consequently, taking the sign of the LLR corresponds to a hard decision detector. The magnitude of the LLR corresponds to reliability information.
At the relay station 1450 in FIG. 16, the decoders 1451 and 1452 determine the LLRs of the corresponding information words u1 and u2. Moreover, FIG. 16 shows that the relay station 1450, the LLRs at the output of the second decoder 1452 are provided to an interleaver 1456, which interleaves the LLRs. The interleaved LLRs from the second decoder are then combined by the combiner 1457 before analog transmission is used to transmit information on the combination to the destination 1470. Reliability information, in terms of the LLRs is therewith provided to the joint decoder at the destination 1470. However, long delays still occur at the relay station 1450 in order to determine the soft information by the two decoders 1451 and 1452.
FIG. 17 illustrates the same scenario as FIG. 16, however, the details on the destination or NodeB are provided. As can be seen from FIG. 17, LLRs are determined at the destination 1470 for the three receive signals y1, y2, and yR by the three detectors 1471, 1472, and 1473. FIG. 17 illustrates the concept of joint iterative decoding. The log likelihood ratio provided by the detector 1471 is, in a first step, provided to a first decoder 1475, in order to determine LLRs on the information word u1. The LLRs provided at the input of the decoder 1475 correspond to a-posteriori knowledge of the transmitted code words. At the output of the decoder 1475, a-priori knowledge on the information word u1 is determined by evaluating the difference of the a-posteriori knowledge and the output of the decoder 1475. The a-priori knowledge is still available in terms of LLRs which can then be combined by the combiner 1476 with the LLRs determined by detector 1473 from the received signal yR on the combination determined at the relay station 1450.
The combination can, for example, be determined by determining a combined LLR for an XOR-combination of the information words u1 and u2. Subsequently, a derivation of the exact combination will be provided which is indicated by . From the a-priori knowledge on the first information word and the LLR on the combination, a-posteriori knowledge on the second information word can be determined, which is de-interleaved by de-interleaver 1477. The de-interleaver 1477 corresponds to the interleaver 1456 at the relay station 1450. The de-interleaved LLR at the output of the de-interleaver 1477 can then be combined with the LLRs detected by detector 1472 from the second receive signal y2, and provided as an input to the second decoder 1478. The second decoder 1478 then provides LLRs on the second information word u2 at its output, from which the a-posteriori knowledge from the detector 1472 and the interleaver 1477 can be deducted for determining a-priori information, which may also be called extrinsic information.
After interleaving 1479, the interleaved LLRs can again be combined with the output of the detector 1473 by combiner 1480. A-posteriori information on the first information word u1 is available at the output of the combiner 1480, which can again be combined with the a-posteriori knowledge at the output of the detector 1471. The above description corresponds to a first iteration loop of the joint iterative decoder, which is similar to the principle of turbo decoding. Multiple iteration loops may be carried out along the lines of the above description in order to determine more reliable information on the information words u1 and u2.
FIG. 18 illustrates the case, where at a relay station 1450 bad or weak radio channels are experienced and accordingly, LLRs are determined, which are equal or close to zero. Consequently, at the destination 1470, the LLRs determined by the detector 1473 equal zero, i.e. only very unreliable information is available. Consequently, the combinations carried out by combiners 1476 and 1480 also yield LLRs, which are zero. Therefore, within the decoder, the LLRs of detector 1473 do not influence the LLRs determined by the detectors 1471 and 1472. In other words, if decoding at the relay station 1450 is very unreliable, decoding at the destination is solely based on the outputs of the detectors 1471 and 1472. The iterative process does not provide any benefits in this case.
FIG. 19 illustrates simulation results on the bit error rate (BER=Bit Error Rate) for the scenario, which is depicted on the left-hand side of FIG. 19. In this scenario two sources 1901 and 1902 transmit signals to a relay station 1903 and a destination 1904. Moreover, on all links signal-to-noise ratios (SNR=Signal-to-Noise Ratio) are given, namely, SNRsr on the links between the sources 1901 and 1902 and the relay station 1903, SNRsd on the links between the sources 1901 and 1902 and the destination 1904, and SNRrd for the link between the relay station 1903 and the destination 1904. On the right-hand side of the FIG. 19, a view chart depicts BER vs. SNR on the links between the sources 1901 and 1902 and the destination 1904. For the simulations, it was assumed that the links are symmetric, i.e. similar SNRs occur on the links of both sources 1901 and 1902 to the relay station 1903. Moreover, for the results depicted on the right-hand side of FIG. 19, it was assumed that SNRsr=5 dB and results are shown for different SNRrd between the relay station 1903 and the destination 1904. The results illustrate that significant benefits can be obtained in BER if the signal quality on the link between the relay station 1903 and the destination 1904 increases.
FIG. 20 illustrates similar simulation results. However, for the results in FIG. 20, it was assumed that the SNR on the links between the sources 1901 and 1903, and the relay station 1903 was 0 dB, i.e. more errors occur at the relay station 1903 than for the case considered in FIG. 19. It can still, however, be observed that gains in BER can be obtained with increasing signal quality on the link between the relay station 1903 and the destination 1904.
FIG. 21 shows a similar scenario using analog transmission from the relay station 1450 as explained with the assistance of FIG. 16. At the bottom of FIG. 21 the combined LLR L(uR) is illustrated. It can be seen from the view chart at the bottom of FIG. 21 that the combined LLR is approximately Gaussian distributed. Since analog transmission is used, large transmit powers need to be utilized, in order to transmit the combined LLR reliably, considering that they are superimposed by AWGN as well.
FIG. 22 illustrates an option for at least partly overcoming the problem of having to utilize large transmission powers. At the relay station 1450, the combined LLRs are processed by signal processor 1458, in which the hyperbolic tangent of the combined LLR is determined and used for analog transmission, also referred to as soft bit transmission in the following. A similar option is illustrated in FIG. 23 in which a quantizer 1459 is used for quantizing the LLRs at the relay station 1450, 1903 respectively. FIG. 23 shows at the top on the right-hand side the scenario as it was discussed above, involving the two sources 1901 and 1902, the relay station 1903, and the destination 1904. For the simulation results depicted on the left-hand side of FIG. 23, it was assumed that the SNR, of the links between the sources 1901 and 1902 and the relay station 1903 is 3 dB. At the bottom right-hand side of FIG. 23, the details of the relay station 1450 or 1903 are depicted, in which the quantizer 1459 is shown.
In the view chart on the left-hand side the probability density of the LLR LR is shown assuming two quantizer regions separated by the dotted line. The two squares represent the quantizer values to be transmitted to the destination 1904. Having only two quantizer regions corresponds to transmitting only one bit per quantized value from the relay station 1903 to the destination 1904. In this scenario it can be observed that almost no degradation due to the quantization occurs with respect to the trans- or mutual information, i.e. almost no information is lost due to quatization.
FIG. 24 shows simulation results on the BER vs. the SNRsd on the link between the sources 1901 or 1902 and the destination 1904. For the simulations, it was assumed that the SNRsr between the sources 1901 and 1902 and the relay station 1903, is 3 dB, for the SNRrd between the relay station 1903 and the destination 1904 0 dB was assumed. The view chart on the left-hand side of FIG. 24 shows BER simulation results for analog transmission indicated by the square markers, soft bit analog transmission indicated by the triangular markers, and quantizer transmission using two quantizer regions, i.e. only one bit per quantizer value by the circular markers. It can be observed that the degradation, when using the quantized values, occurs only for high SNRs between the sources and the destination, whereas for rather low SNRs between the sources and the destination, transmitting the quantized value provides improvements in the BER, which is due to the AWGN taking higher effect on the analog transmission for low SNRs.
FIG. 25 illustrates another simulation scenario, in which five quantizer regions were assumed for a scenario, in which the SNRsr=0 dB, i.e. it is lower than in the above discussed scenario. Since five quantizer regions were assumed, an average of 2.3 bits have to be transmitted per quantized value after source coding. The view chart on the left-hand side of FIG. 25 shows the probability density of the LLRs at the input of the quantizer 1459, the quantizer regions are separated by the dotted lines, and the representative values are indicated by square markers.
FIG. 26 shows simulation results on the BER when SNRsr=3 dB is assumed for the links between the sources 1901 and 1902, and the relay station 1903, and an SNR of 0.44 dB is assumed for the link between the relay station 1903 and the destination 1904. The view graph on the left-hand side of FIG. 26 shows simulation results for analog transmission indicated by square markers, for soft bit transmission indicated by triangular markers and quantized transmission by circular markers. The simulation results indicate that no degradation at all can be observed when quantization is used.
FIG. 27 illustrates another soft relay and network coding concept wherein quantized transmission from the relay station 1450 to the destination 1470 is used. An equation is illustrated at the top of FIG. 27, which details the combination of the LLRs by the combiner 1457. The output of the combiner 1457 corresponds to the LLR, which can be obtained by an XOR combination of the information words u1 and u2, and which is indicated in the equation at the top of FIG. 27 by an arrow operator pointing to the left. Moreover, FIG. 27 illustrates, within the relay station 1450, the quantizer 1459 for quantizing the combined LLRs to Z, the source coder 1460 for source coding the quantized combined LLRs and an encoder 1461 for channel encoding the source coded combined LLRs before transmission to the destination 1470.
In the example depicted in FIG. 27, it is the task of the quantizer 1459 to compress Lr as much as possible while preserving the relevant information about uR=u1⊕u2 in the quantized signal Z. This is expressed by the equation at the bottom of FIG. 27 which indicates that the distribution of the quantizer region Z for a given LLR should be chosen, so as to minimize the difference between trans-information I(Lr,Z) between the LLR Lr and the chosen quantizer Z, and the trans-information I(Ur,Z) between the combined information words Ur and the chosen quantizer Z, which is expressed in the equation in terms of a Lagrangian problem based on factor β.
FIG. 28 illustrates a similar scenario, but shows that if one of the links between the encoders 1410; 1420 and the relay station 1450 degrades, which is exemplified as the link between encoder 1410 and the relay station 1450 in FIG. 28, the combined LLR becomes zero. Therefore, the SNR on the first hop, on the link between the sources and the relay station can be taken into account in the design of the quantizer.
FIG. 29 shows another relay station 1450 in which the LLRs are jointly quantized by quantizer 1459 in order to take the signal quality into account, for which FIG. 30 illustrates the details of the quantizer. On the left-hand side of FIG. 30, a quantizer for symmetric links is shown for which the mutual information after decoding equals 1.98 bits. The relevant mutual information or trans-information after quantization equals 1.93 bits, and since only two quantizer regions are utilized, only 1-bit is required for encoding the source encoded bits on the link between the relay station 1450 and the base station, or destination 1470. The quantizer regions are illustrated in the diagram at the top of FIG. 30 on the left hand side.
On the right-hand of FIG. 30, a quantizer for asymmetric links is shown, for which the mutual information after decoding equals 1.16 bits. The relevant mutual information after quantization equals 1.08 bits, and since five quantizer regions are utilized, an average of 2.1 bits per source coded bit is required.